Objective To compare the CT findings of different phases in pediatric hepatoblastoma (HB) based on PRETEXT system in order to optimize pediatric HB CT scan protocol. Methods A total of 58 HB patients who were surgical and pathological diagnosed from January 2015 to December 2016 were analyzed. Pre-operation CT exams were analyzed respectively. Observing items included tumor size, intra-abdominal invasion, bleeding, intrahepatic metastasis, lymphatic metastasis, metastasis (except lymphatic in abdomen) main portal vein, three main hepatic vein, inferior vena cava (IVC) invasion, para-tumor hepatic arteries, and its branches. All image findings were compared to pathological and surgical findings to calculate the agreement rate. Exact Fisher test and R × C χ2 test were used. Results According to the surgery and pathological results, the agreement rate of tumor size was n=40 (68.9%) at non-contrast phase, n=43 (74.1%) at artery phase and n=52 (91.2%) at venous phase. Venous phase was adaptive for observing tumor size (χ2=8.16,P=0.018). For main portal vein, three main hepatic vein, and IVC invasion, none was found at both non-contrast and artery phase. N=12 (20.7%, P<0.001) was found at venous phase. For para-tumor hepatic arteries, and its branches, none was found at non-contrast phase. N=46 (79.3%) was found at artery phase. N=17 (29.3%) was found at venous phase. Artery phase was adaptive for observing (P<0.001). There was no statistical significant difference in intrahepatic metastasis, lymphatic metastasis and metastasis. Conclusions Suspected pediatric HB, artery and venous phase CT scan would meet the clinical requirement, there was no need for non-contrast pahse. Follow up cases, a single venous phase was enough. Venous phase contributed much more information on tumor size and high risk prognosis evaluation.

Objective To compare the X-ray features between Hirschsprung alied disease (HAD)and Hirschsprung disease ( HD), and analyze the differentiations. Methods From December 2004 to December 2009, nineteen cases of HAD, aged from 30 days to 10 years (median, 14 months), received barium enema examinations in our institution. Other 19 cases with HD, also received barium enema examinations, were chosen randomly. They were aged from 42 days to 8 years ( median, 8 months). The imaging features of HAD and HD were analyzed retrospectively. The incidence rate of colon stenosis,"truncation sign" and spasm notch and R/C ratio (the longest diameter of rectum/colon) were calculated and compared between these two groups. In all these cases, diagnosis was confirmed by postoperative histopathology. The position of barium retained was also evaluated. These parameters of both groups were compared by x2 and Fisher test. Results There was statistical significance in the incidence rate of colon stenosis between HAD (9/19) and HD (18/19) (x2 = 10.364, P ＜0.01). However, there was no statistical significance in "truncation sign" and spasm notch between HAD (4/19 and 3/19, respectively)and HD ( 1/19 and 1/19, respectively) (P ＞0. 05 for both). R/C ratio was 0. 42 ±0. 15 in HAD group and 0.29±0. 12 in HD group, and there was statistical significance between them (t =2.892,P＜0.01). In HAD group, barium retained in distal sigmoid colon in 1 case (1/19), in distal descending colon in 7 cases (7/19), in distal transverse colon in 1 case (1/19), in total colon in 6 cases (6/19); However, in HD group, barium retained in distal rectum in 3 cases (3/19), in distal sigmoid colon in 13 cases ( 13/19), in distal descending colon in 3 cases (3/19). Conclusions There were some differences in the imaging features between HAD and HD though they presented similar clinic experience. HAD cases presented a lower incidence rate of colon stenosis and a higher R/C ratio than HD cases. In HAD cases, the most common site of barium retained is distal descending colon, while in HD cases, it is distal sigmoid colon.

Objective To explore the CT findings of pediatric hepatoblastoma and its correlation with pathological subtypes.Methods CT findings and pathological characteristics of 110 patients with hepatoblastoma confirmed by pathology were retrospectively analyzed.Results The locations of the tumor were right lobe (67/110,60.90％),right and left lobe (25/110,22.72％),left lobe (15/110,13.63％) and caudate lobe (3/110,2.72％).The average tumor size was (287.14±272.36) cm3.Most cases were solitary (94/110,85.45％) and round shape (96/110,87.27％).Most cases were well defined (86/110,78.18 ％).Necrosis were irregular in 102 cases,calcification were in 60 cases.Lung metastases were common (23/110,20.90 ％) and vessel involvement were common (56/110,50.90 ％).Lymph node metastasis was in 5 cases.Calcification and homogeneous enhancement in different pathological types had statistically significance (both P ＜0.001).Conclusion CT is helpful for pre-operation and pathological diagnose.

Objective:To investigate the differences between Tanner-Whitehouse (TW)3-Carpal and TW3-RUS(radius, ulna and short bone)-based artificial intelligence (AI)-assisted bone age assessment system using real world data.Methods:The image data of 262 children who received X-ray examination of left wrist in the Affiliated Children′s Hospital, Capital Institute of Pediatrics from July to September 2021 were retrospectively collected. The AI bone age assistant methods based on TW3-RUS and TW3-Carpal criteria were used to obtain the bone age results, respectively. Two senior pediatric radiologists evaluated the bone age on the basis of TW3-RUS and TW3-Carpal criteria, and the averaged values of two reviewers was calculated and taken as the gold standard reference. The cases were stratified into six age groups at 3-year intervals according to the gold standard reference, including 1-3 ( n=10), 4-6 ( n=35), 7-9 ( n=70), 10-12 ( n=118), 13-15 ( n=27) and 16-18 ( n=2) years old groups. Intraclass correlation coefficient (ICC) was used to evaluate the consistency between AI results and the gold standard bone age results. Pearson correlation method was used to measure the reliability between AI results and the gold standard results. The difference of bone age results between using TW3-RUS and TW3-Carpal criteria in different age groups was compared using paired t-test. Results:As for the whole sample, the results based on TW3-RUS criteria were 8.9±3.1 years old for AI assessment and 8.7±2.9 years old for the golden standard reference, with the ICC of 0.983; and the results based on TW3-Carpal criteria were 8.7±3.0 years old for AI and 8.8±2.8 years old for the golden standard reference, with the ICC of 0.976. Positive correlation were found in both TW3-RUS ( r=0.985, P<0.001) and TW3-Carpal criteria groups ( r=0.978, P<0.001). There were significant differences between TW3-RUS and TW3-Carpal at age groups of 7-9( t=-3.36, P=0.001), 10-12( t=-1.77, P=0.046), and 13-15 years old ( t=1.84, P=0.040). The bone age assessment using TW3-RUS and TW3-Carpal criteria were both in good agreement with the gold standard reference in age group of 4-6 years old (ICC=0.929 and 0.940), as well as in age group of 7-9 years old (ICC=0.882 and 0.927, respectively), with the results using TW3-Carpal criteria were slightly higher. As for the age groups of 10-12 and 13-15 years old, the method using TW3-RUS criteria showed excellent agreement with the gold standard reference (ICC=0.962 and 0.963, respectively), which were better than the performance of method using TW3-Carpal criteria (ICC=0.744 and 0.605, respectively). Conclusions:AI-assisted bone age system based TW3-Carpal and TW3-RUS criteria both show good reliability and accuracy in the bone age measurements. The AI method based TW3-Carpal criteria shows better performance in age group of 4-9 years old, while the method based on TW3-RUS criteria may be better for children of age 10-15 years old.

Objective:Based on the questionnaire, to analyze the current status of children′s bone age assessment in China, especially the application of artificial intelligence (AI)-assisted bone age assessment system in the clinic.Methods:This was a cross-sectional study. The questionnaire was adapted by ourselves through the literature method and expert interview method, and the whole volume included 22 questions, which were released in the form of WeChat applet questionnaire star to the physician groups of several associations and entrusted to the radiology and paediatricians with senior titles. The results of the different types of questions were summarised and analyzed, and the chi-square test was used to compare the count data.Results:A total of 450 valid questionnaires were collected from 162 medical institutions in 26 provinces and cities and autonomous regions, of which 232 (51.6%) were from 87 (53.7%) tertiary hospitals and 218 (48.4%) from 75 (46.3%) secondary hospitals. Of the respondents, 115 (25.6%) were senior, 137 (30.4%) middle and 198 (44.0%) junior. Child bone age measurement was performed at 75.9% (66/87) of tertiary care organizations and 26.7% (20/75) of secondary care organizations, and the difference was statistically significant ( χ2=39.10, P<0.001). Left wrist radiographs were predominantly used for bone age assessment (76.0%, 123/162), with 72.8% (118/162) of sites using the ATLAS method of assessment and 17.9% (29/162) using the scoring method. A total of 98.4% (443/450) of respondents agreed that AI technology should be used to assist in bone age assessment, but only 9.3% (15/162) of healthcare organizations used AI-assisted technology. Conclusion:At present, bone age assessment is widely used in medical institutions, but there are problems with non-standardized examination methods, inconsistent assessment standards, and imprecise assessment results. Expectations for AI technology-assisted diagnosis exist among a wide range of physicians, but there are fewer users.